This blog post is the third and final part in a series of posts on creating advanced search applications with Spinque and the Open Data Node. We go to the beginning of the chain and describe the transformation and publication of the datasets itself. Using the Open Data Node we transformed, integrated and published five datasets.

With more and more Linked Open Data published, it’s harder for users to consume them. If you publish just one dataset it’s pretty clear what you are offering and what they could consume. With a larger knowledge base, they have to start by learning its structure. In particular, they need to recognize in which dataset they could find the information they are looking for. That’s why we wanted to come up with a tool that would visually help users to explore a knowledge base and more importantly to enable them to visualise its content in a traditional way. Such a tool is our LDVMi, a part of the ODN platform.

In the previous article from Mr. Lubor Illek (Security concerns of Open Data publishing), we’ve outlined some security concerns which apply to publication of Open Data, regarding security of the IT environment of the publisher and security (in the sense of „protection“) of the published data. In this article we describe in more detail what exactly Open Data Node (ODN) does for publishers in that regard.